CONTROL TOWER AND ENTERPRISE MANAGEMENT PLATFORM WITH ROBOTIC PROCESS AUTOMATION SYSTEMS MANAGING PRODUCT OUTCOMES AND ACTIVITIES

Abstract

A value chain system that provides recommendations for designing a logistics system generally includes a machine learning system that trains machine-learned models that output logistics design recommendations based on training data sets that each respectively defines one or more features of a respective logistic system and an outcome relating to the respective logistics system; an artificial intelligence system that receives a request for a logistics system design recommendation and determines the logistics system design recommendation based on one or more of the machine-learned models and the request; and a digital twin system that generates an environment digital twin of a logistics environment that incorporates the logistics system design recommendation, and one or more physical asset digital twins of physical assets. The digital twin system executes a simulation based on the logistics environment digital twin, the one or more physical asset digital twins.

Claims

1. An information technology system, comprising: a cloud-based management platform with a micro-services architecture, the platform having a set of interfaces that are configured to access and configure features of the platform, a set of network connectivity facilities that are configured to direct a set of value chain network entities to connect to the features of the platform, a set of adaptive intelligence facilities that are configured to automate a set of capabilities of the platform related to at least one of the value chain network entities and the features of the platform, or a set of monitoring facilities that are configured to monitor the value chain network entities, wherein the interfaces, the network connectivity facilities, the adaptive intelligence facilities, and the monitoring facilities are coordinated for monitoring and management of the value chain network entities; a set of applications that are configured to direct an enterprise to manage the value chain network entities of the platform from a point of origin to a point of customer use; and a set of microservices layers including an application layer supporting at least one supply chain application and at least one demand management application, wherein the microservices layers include a robotic process automation layer that uses information collected by a data collection layer and a set of outcomes and activities involving the applications of the application layer to automate a set of actions for at least a subset of the applications with respect to the value chain network entities of the platform.

2. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves selection of a quantity of product for an order.

3. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves selection of a carrier for a shipment.

4. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves at least one of a selection of a vendor for a component or a vendor for a finished goods order.

5. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves selection of a variation of a product for marketing.

6. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves selection of an assortment of goods for a shelf.

7. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves determination of a price for a finished good.

8. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves configuration of at least one of a service offer related to a product or configuration of product bundle.

9. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves at least one of configuration of a product kit, a product package, a product display, a product image, or a product description.

10. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves configuration of a website navigation path related to a product.

11. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves determination of an inventory level for a product.

12. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves selection at least one of a logistics type or a schedule for product delivery.

13. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves configuration of a logistics schedule.

14. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves configuration of a set of inputs for machine learning.

15. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves at least one of preparation of product documentation or preparation of disclosures about a product.

16. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves configuration of a product for a set of local requirements.

17. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves configuration of a set of products for compatibility.

18. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves configuration of a request for proposals.

19. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves ordering of equipment for a at least one of a warehouse or a fulfillment center.

20. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves at least one of classification of a product defect in an image or inspection of a product in an image.

21. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves inspection of product quality data from a set of sensors.

22. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves inspection of data from a set of onboard diagnostics on a. product.

23. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves review of sensor data from environmental sensors in a set of supply chain environments.

24. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves selection of inputs for a digital twin.

25. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves selection of outputs from a digital twin.

26. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves selection of visual elements for presentation in a digital twin.

27. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves diagnosis of sources of at least one of delay, congestion, or scarcity in a supply chain.

28. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves diagnosis of sources of cost overruns in a supply chain.

29. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves diagnosis of sources of product defects in a supply chain.

30. The system of claim 1, wherein one of the actions automated by the robotic process automation layer involves prediction of maintenance requirements in supply chain infrastructure.

31. The system of claim 1, wherein the robotic process automation layer automates a process including at least one of selection of a quantity of product for an order, selection of a carrier for a shipment, selection of a vendor for a component, selection of a vendor for a finished goods order, selection of a variation of a product for marketing, selection of an assortment of goods for a shelf, determination of a price for a finished good, configuration of a service offer related to a product, configuration of product bundle, configuration of a product kit, configuration of a product package, configuration of a product display, configuration of a product image, configuration of a product description, configuration of a website navigation path related to a product, determination of an inventory level for a product, selection of a logistics type, configuration of a schedule for product delivery, configuration of a logistics schedule, configuration of a set of inputs for machine learning, preparation of product documentation, preparation of disclosures about a product, configuration of a product for a set of local requirements, configuration of a set of products for compatibility, configuration of a request for proposals, ordering of equipment for a warehouse, ordering of equipment for a fulfillment center, classification of a product defect in an image, inspection of a product in an image, inspection of product quality data from a set of sensors, inspection of data from a set of onboard diagnostics on a. product, inspection of diagnostic data from an Internet of Things system, review of sensor data from environmental sensors in a set of supply chain environments, selection of inputs for a digital twin, selection of outputs from a digital twin, selection of visual elements for presentation in a digital twin, diagnosis of sources of delay in a supply chain, diagnosis of sources of scarcity in a supply chain, diagnosis of sources of congestion in a supply chain, diagnosis of sources of cost overruns in a supply chain, diagnosis of sources of product defects in a supply chain, or prediction of maintenance requirements in supply chain infrastructure.